Adressing review feedback

Signed-off-by: Ryan Lettieri <[email protected]>

Author: RyanLettieri

examples/README.md

@@ -1,6 +1,6 @@
 # Examples
 
-This directory contains examples of how to author durable orchestrations using the Durable Task Python SDK. There are two backends that are compatible with the Durable Task Python SDK: The Dapr sidecar, and the Durable Task Scheduler (DTS)
+This directory contains examples of how to author durable orchestrations using the Durable Task Python SDK. There are two backends that are compatible with the Durable Task Python SDK: The Dapr sidecar, and the Durable Task Scheduler (DTS).
 
 ## Prerequisites for using Dapr
 

examples/dts/README.md

@@ -0,0 +1,35 @@
+# Examples
+
+This directory contains examples of how to author durable orchestrations using the Durable Task Python SDK in conjunction with the Durable Task Scheduler (DTS).
+
+## Prerequisites
+
+All the examples assume that you have a Durable Task Scheduler taskhub created.
+
+The simplest way to create a taskhub is by using the az cli commands:
+
+1. Create a scheduler:
+    az durabletask scheduler create --resource-group <testrg> --name <testscheduler> --location <eastus> --ip-allowlist "[0.0.0.0/0]" --sku-capacity 1 --sku-name "Dedicated" --tags "{}"
+
+2. Create your taskhub
+    az durabletask taskhub create --resource-group <testrg> --scheduler-name <testscheduler> --name <testtaskhub>
+
+3. Retrieve the endpoint for the scheduler. This can be done by locating the taskhub in the portal.
+
+4. Set the appropriate environment variables for the TASKHUB and ENDPOINT
+
+```sh
+export TASKHUB=<taskhubname>
+```
+
+```sh
+export ENDPOINT=<taskhubEndpoint>
+```
+
+## Running the examples
+
+With one of the sidecars running, you can simply execute any of the examples in this directory using `python3`:
+
+```sh
+python3 dts_activity_sequence.py
+```

examples/dts_activity_sequence.py renamed to examples/dts/dts_activity_sequence.py

@@ -41,22 +41,22 @@ def sequence(ctx: task.OrchestrationContext, _):
 if endpoint:
     print(f"The value of ENDPOINT is: {endpoint}")
 else:
-    print("ENDPOINT is not set. Please set the ENDPOINT environment variable to the endpoint of the taskhub")
-    print("If you are using windows powershell, run the following: $env:ENDPOINT=\"<taskhubEndpoint>\"")
-    print("If you are using bash, run the following: export ENDPOINT=\"<taskhubEndpoint>\"")
+    print("ENDPOINT is not set. Please set the ENDPOINT environment variable to the endpoint of the scheduler")
+    print("If you are using windows powershell, run the following: $env:ENDPOINT=\"<schedulerEndpoint>\"")
+    print("If you are using bash, run the following: export ENDPOINT=\"<schedulerEndpoint>\"")
     exit()
 
 
 default_credential = DefaultAzureCredential()
 # Define the scope for Azure Resource Manager (ARM)
 arm_scope = "https://durabletask.io/.default"
 
-# Retrieve the access token
+# Retrieve the access token. Note that this approach doesn't support token refresh and can't be used in production.
 access_token = "Bearer " + default_credential.get_token(arm_scope).token
-# create a client, start an orchestration, and wait for it to finish
+
 metaData: list[tuple[str, str]] = [
-    ("taskhub", taskhub_name), # Hardcode for now, just the taskhub name
-    ("authorization", access_token) # use azure identity sdk for python
+    ("taskhub", taskhub_name),
+    ("authorization", access_token)
 ]
 # configure and start the worker
 with worker.TaskHubGrpcWorker(host_address=endpoint, metadata=metaData, secure_channel=True) as w: